Optimal UAV Hangar Locations for Emergency Services Considering Restricted Areas

Research output: Contribution to journalResearch articleContributedpeer-review

Abstract

With unmanned aerial vehicle(s) (UAV), swift responses to urgent needs (such as search and rescue missions or medical deliveries) can be realized. Simultaneously, legislators are establishing so-called geographical zones, which restrict UAV operations to mitigate air and ground risks to third parties. These geographical zones serve particular safety interests but they may also hinder the efficient usage of UAVs in time-critical missions with range-limiting battery capacities. In this study, we address a facility location problem for up to two UAV hangars and combine it with a routing problem of a standard UAV mission to consider geographical zones as restricted areas, battery constraints, and the impact of wind to increase the robustness of the solution. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimum UAV mission trajectories are computed with an A* algorithm, considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image-processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimum UAV hangar locations, we maximize accessibility while minimizing the service times to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimum UAV hangar locations.
Keywords: optimum UAV hangar location; facility location problem; search & rescue mission planning; UAS geographical zone; open source georeferenced data

Details

Original languageEnglish
Article number203
Number of pages19
JournalDrones
Volume7(2023)
Issue number3
Publication statusPublished - 16 Mar 2023
Peer-reviewedYes

External IDs

unpaywall 10.3390/drones7030203
Mendeley 8936a5ae-4432-3038-9d08-b7e37f26f788
WOS 000955091900001
Scopus 85152027050

Keywords

Keywords

  • Facility location problem, Open source georeferenced data, Search & rescue mission planning, UAS geographical zone, optimum UAV hangar location, open source georeferenced data, search & rescue mission planning, facility location problem